AWS Data Engineer

This role is ideal for someone who owns the end-to-end data lifecycle --- from ingestion and transformation to analytics, reporting, and insight generation --- and has experience delivering production-grade data solutions in enterprise environments.

Key Responsibilities:

Data Engineering & Platform Development

• Design, build, and maintain enterprise-scale data pipelines using AWS and Snowflake

• Architect and optimize cloud-native data platforms leveraging Amazon S3, Snowflake, Redshift, Athena, and EMR

• Develop robust ETL/ELT pipelines using AWS Glue, Lambda, Step Functions, Airflow, Spark, or similar tools

• Implement and manage Snowflake data models, schemas, and performance optimization (clustering, pruning, warehouse sizing)

• Integrate data from multiple enterprise sources (relational databases, APIs, SaaS platforms, event streams)

• Ensure data quality, observability, governance, and security across pipelines

• Optimise performance, scalability, and cost efficiency across AWS and Snowflake environments

Data Analysis & Analytics Enablement

• Perform exploratory, ad-hoc, and deep-dive data analysis using Snowflake and SQL

• Design and maintain analytical datasets, KPIs, and metrics layers

• Partner with business stakeholders to translate requirements into actionable insights

• Build and support dashboards, reports, and self-service analytics

• Validate data accuracy and ensure consistency across Snowflake, BI tools, and downstream consumers

• Support executive, operational, and enterprise reporting use cases

Required Qualifications

• 5+ years of experience in Data Engineering, Analytics Engineering, or related roles

• Strong hands-on experience with Snowflake as an enterprise data warehouse

• Strong experience with AWS cloud services, including:

  • S3, Redshift, Athena, Glue, Lambda, RDS, DynamoDB, EMR

• Advanced proficiency in SQL, especially for analytical workloads in Snowflake

• Strong programming skills in Python (pipelines, analysis, automation)

• Experience building and operating production-grade ETL/ELT pipelines

• Solid understanding of:

  • Data warehousing and dimensional modeling

  • Analytical data modeling and metric design

• Proven experience delivering large-scale or enterprise data projects